The present invention relates to a computerized item and peer recommendation system directed toward industry professionals. The system maintains the declared profile of professionals and a history of actions taken by professionals within a given field of expertise, and uses the combination of declared profile and history of actions to recommend items or peers to other professionals within the same or a similar field. The item recommendations can include, for example, documents to be reviewed, events to attend, search keywords that may be of interest, etc.
Various tools for maintaining documentation in various fields are known in the art. For example, U.S. Pat. No. 7,035,838 to Nelson et al. discloses methods and systems for organizing information stored within a computer network-based system. Documentation relating to a plurality of topics and a list of experts on a plurality of topics is stored in a centralized database. A user interface enables a user to search the database for a specific item of information by at least one of a work function, a functional category and a community.
Prior art systems such as those referred to above generally provide a broad spectrum of choices of information, which can be overwhelming. As a result, the most pertinent information may be overlooked or not viewed by the user. If the user is particularly diligent, he or she may try to sort through the many potential articles or other documents that are presented to attempt to find the most relevant ones. Such diligence can waste the user's time and may not result in the best match being found. Often, the user will settle for less relevant information instead of carefully considering each of the many potential matches presented.
It would be advantageous to provide improved apparatus and methods for obtaining relevant information that can assist a user in staying current in a profession and/or can assist in solving a business or technical problem. It would be further advantageous to provide such a system that presents highly relevant information to individual users without overwhelming the user with too much information.
The present invention provides an item and peer recommendation engine which uses a combination of cluster filtering algorithms, collaborative filtering algorithms, search algorithms, and dynamic expert verification algorithms that enjoys the aforementioned and other advantages.